Fixed-Time Sliding Mode Control With Varying Exponent Coefficient for Modular Reconfigurable Flight Arrays

The modular system can change its physical structure by self-assembly and self-disassembly between modules to dynamically adapt to task and environmental requirements. Recognizing the adaptive capability of modular systems, we introduce a modular reconfigurable flight array(MRFA) to pursue a multifunction aircraft fitting for diverse tasks and requirements,and investigate the attitude control and the control allocation problem by using the modular reconfigurable flight array as a platform. First, considering the variable and irregular topological configuration of the modular array, a center-of-mass-independent flight array dynamics model is proposed to allow control allocation under over-actuated situations. Secondly, in order to meet the stable, fast and accurate attitude tracking performance of the MRFA, a fixed-time convergent sliding mode controller with state-dependent variable exponent coefficients is proposed to ensure fast convergence rate both away from and near the system equilibrium point without encountering the singularity. It is shown that the controller also has fixed-time convergent characteristics even in the presence of external disturbances. Finally,simulation results are provided to demonstrate the effectiveness of the proposed modeling and control strategies.

Aerodynamic Effects Compensation on Multi-Rotor UAVs Based on a Neural Network Control Allocation Approach

This paper shows that the aerodynamic effects can be compensated in a quadrotor system by means of a control allocation approach using neural networks.Thus,the system performance can be improved by replacing the classic allocation matrix,without using the aerodynamic inflow equations directly.The network training is performed offline,which requires low computational power.The target system is a Parrot MAMBO drone whose flight control is composed of PD-PID controllers followed by the proposed neural network control allocation algorithm.Such a quadrotor is particularly susceptible to the aerodynamics effects of interest to this work,because of its small size.We compared the mechanical torques commanded by the flight controller,i.e.,the control input,to those actually generated by the actuators and established at the aircraft.It was observed that the proposed neural network was able to closely match them,while the classic allocation matrix could not achieve that.The allocation error was also determined in both cases.Furthermore,the closed-loop performance also improved with the use of the proposed neural network control allocation,as well as the quality of the thrust and torque signals,in which we perceived a much less noisy behavior.

Control allocation for a class of morphing aircraft with integer constraints based on Lévy flight

Aiming at tracking control of a class of innovative control effector(ICE) aircraft with distributed arrays of actuators, this paper proposes a control allocation scheme based on the Lévy flight.Different from the conventional aircraft control allocation problem,the particular characteristic of actuators makes the actuator control command totally subject to integer constraints. In order to tackle this problem, first, the control allocation problem is described as an integer programming problem with two desired objectives. Then considering the requirement of real-time, a metaheuristic algorithm based on the Lévy flight is introduced to tackling this problem. In order to improve the searching efficiency, several targeted and heuristic strategies including variable step length and inherited population initialization according to feedback and so on are designed. Moreover, to prevent the incertitude of the metaheuristic algorithm and ensure the flight stability, a guaranteed control strategy is designed. Finally, a time-varying simulation model is introduced to verifying the effectiveness of the proposed scheme. The contrastive simulation results indicate that the proposed scheme achieves superior tracking performance with appropriate actuator dynamics and computational time, and the improvements for efficiency are active and the parameter settings are reasonable.

Control allocation algorithm for over-actuated electric vehicles

A control allocation algorithm based on pseudo-inverse method was proposed for the over-actuated system of four in-wheel motors independently driving and four-wheel steering-by-wire electric vehicles in order to improve the vehicle stability. The control algorithm was developed using a two-degree-of-freedom(DOF) vehicle model. A pseudo control vector was calculated by a sliding mode controller to minimize the difference between the desired and actual vehicle motions. A pseudo-inverse controller then allocated the control inputs which included driving torques and steering angles of the four wheels according to the pseudo control vector. If one or more actuators were saturated or in a failure state, the control inputs are re-allocated by the algorithm. The algorithm was evaluated in Matlab/Simulink by using an 8-DOF nonlinear vehicle model. Simulations of sinusoidal input maneuver and double lane change maneuver were executed and the results were compared with those for a sliding mode control. The simulation results show that the vehicle controlled by the control allocation algorithm has better stability and trajectory-tracking performance than the vehicle controlled by the sliding mode control. The vehicle controlled by the control allocation algorithm still has good handling and stability when one or more actuators are saturated or in a failure situation.

Adaptive Neural Network Control with Control Allocation for A Manned Submersible in Deep Sea

This paper thoroughly studies a control system with control allocation for a manned submersible in deep sea being developed in China. The proposed control system consists of a neural-network-based direct adaptive controller and a dynamic control allocation module. A control energy cost function is used as the optimization criteria of the control allocation module, and weighted pseudo-inverse is used to find the solution of the control allocation problem. In the presence of bounded unknown disturbance and neural networks approximation error, stability of the closed-loop control system of manned submersible is proved with Lyaponov theory. The feasibility and validity of the proposed control system is further verified through experiments conducted on a semi-physical simulation platform for the manned submersible in deep sea.

Control allocation for aircraft with input constraints based on improved cuckoo search algorithm

The control allocation problem of aircraft whose control inputs contain integer constraints is investigated. The control allocation problem is described as an integer programming problem and solved by the cuckoo search algorithm. In order to enhance the search capability of the cuckoo search algorithm, the adaptive detection probability and amplification factor are designed. Finally, the control allocation method based on the proposed improved cuckoo search algorithm is applied to the tracking control problem of the innovative control effector aircraft. The comparative simulation results demonstrate the superiority and effectiveness of the proposed improved cuckoo search algorithm in control allocation of aircraft.

Combined Control Allocation and Sliding Mode Control in the Dynamic Control of a Vehicle with Eight In-Wheel Motors

An eight wheel independently driving steering（8 WIDBS）electric vehicle is studied in this paper.The vehicle is equipped with eight in-wheel motors and a steer-by-wire system.A hierarchically coordinated vehicle dynamic control（HCVDC）system,including a high-level vehicle motion controller,a control allocation,an inverse tire model and a lower-level slip/slip angle controller,is proposed for the over-actuated vehicle system.The high-level sliding mode vehicle motion controller is designed to produce desired total forces and yaw moment,distributed to longitudinal and lateral forces of each tire by an advanced control allocation method.And the slip controller is designed to use a sliding mode control method to follow the desired slip ratios by manipulating the corresponding in-wheel motor torques.Evaluation of the overall system is accomplished by sine maneuver simulation.Simulation results confirm that the proposed control system can coordinate among the redundant and constrained actuators to achieve the vehicle dynamic control task and improve the vehicle stability.

Autonomous Control Reconfiguration of Aerospace Vehicle Based on Control Effectiveness Estimation

Future aerospace vehicles （ASV） are designed to fly in both inner and extra atmospheric fields, which requires autonomous adaptability to the uncertainties emanated from abrupt faults and continuously time-varying environments. An autonomous control reconfiguration scheme is presented for ASV to deal with the uncertainties on the base of control effectiveness estimation. The on-line estimation methods for the time-varying control effectiveness of linear control system are investigated. Some sufficient conditions for the estimable system are given for different cases. There are proposed corresponding on-line estimation algorithms which are proved to be convergent and robust to noise using the least-square-based methods. On the ground of fuzzy logic and linear programming, the control allocation algorithms, which are able to implement the autonomous control reconfiguration through the redundant actuators, are put forward. Finally, an integrated system is developed to verify the scheme and algorithms by way of numerical simulation and analysis.

Novel robust control framework for morphing aircraft

This paper develops a robust control methodology for a class of morphing aircraft,which is called innovative control effector（ICE） aircraft.For the ICE morphing aircraft,the distributed arrays of hundreds of shape-change devices are employed to stabilize and maneuver the air vehicle.Because the morphing aircraft have the inherent uncertainty and varying dynamics due to the alteration of their configuration,a desired control performance can not be satisfied with a fixed feedback controller.Therefore,a novel control framework including an adaptive flight control law and an adaptive allocation algorithm is proposed.Firstly,a state feedback adaptive control law is designed to guarantee closed-loop stability and state tracking in the presence of uncertain dynamics caused by the wing shape change due to different flight missions.In the control allocation,many distributed arrays are managed in an optimal way to improve the robustness of the system.The scheme is used to an uncertain morphing aircraft model,and the simulation results demonstrate their performance.

A Lyapunov-based three-axis attitude intelligent control approach for unmanned aerial vehicle

A novel Lyapunov-based three-axis attitude intelligent control approach via allocation scheme is considered in the proposed research to deal with kinematics and dynamics regarding the unmanned aerial vehicle systems.There is a consensus among experts of this field that the new outcomes in the present complicated systems modeling and control are highly appreciated with respect to state-of-the-art.The control scheme presented here is organized in line with a new integration of the linear-nonlinear control approaches,as long as the angular velocities in the three axes of the system are accurately dealt with in the inner closed loop control.And the corresponding rotation angles are dealt with in the outer closed loop control.It should be noted that the linear control in the present outer loop is first designed through proportional based linear quadratic regulator(PD based LQR) approach under optimum coefficients,while the nonlinear control in the corresponding inner loop is then realized through Lyapunov-based approach in the presence of uncertainties and disturbances.In order to complete the inner closed loop control,there is a pulse-width pulse-frequency(PWPF) modulator to be able to handle on-off thrusters.Furthermore,the number of these on-off thrusters may be increased with respect to the investigated control efforts to provide the overall accurate performance of the system,where the control allocation scheme is realized in the proposed strategy.It may be shown that the dynamics and kinematics of the unmanned aerial vehicle systems have to be investigated through the quaternion matrix and its corresponding vector to avoid presenting singularity of the results.At the end,the investigated outcomes are presented in comparison with a number of potential benchmarks to verify the approach performance.

Robust-augmentation nonlinear dynamic inversion control of over-actuated coaxial high-speed helicopter in transition mode

As the elevator and rudder can be used actively for control,in addition to the rotors,Coaxial High-speed Helicopters(CHHs)have the problems of control redundancy and changing control authority in the transition mode.This paper presents a robust-augmentation transitioning flight control design for a CHH under the adverse conditions of parametric uncertainties and external disturbances.First,based on control characteristic analysis,an Adaptive Filtered Nonlinear Dynamic Inversion(AFNDI)controller is proposed for the angular rate to handle the effect of unknown unstructured uncertainties and external turbulence.Theoretical analysis proves that the presented angular rate controller can guarantee steady-state and transient performance.Furthermore,the attitude angle and velocity controllers are also added.Then,an Incremental-based Nonlinear Prioritizing Control Allocation(INPCA)method is designed to take into account control surface transition and changing control authority,which efficiently distributes the required moments between coaxial rotors and aero-surfaces,and avoids the control reversal problem of the yaw channel.In the proposed control architecture,the low-pass filter is introduced to alleviate the adverse influence of time delay and measurement noise.Finally,the effectiveness of the proposed controller is demonstrated through nonlinear numerical simulations,and is compared with existing methods.Simulation results show that the proposed control law can improve both capabilities of disturbance rejection and fast response,and works satisfactorily for the CHH transitioning control characteristic.

Coupled funnel control for supersonic tailless aerial vehicle on penetrating counter air

Supersonic Tailless Aerial Vehicles(STAVs)will become an essential force in Penetrating Counter Air(PCA),but STAVs do not have the traditional horizontal and vertical tails,making pitch and yaw control difficult.The attack angle and the sideslip angle need to be limited to ensure that the engine inlet and the aerodynamic rudder at the rear of the vehicle can work properly,which is the so-called security constraints.In addition,the tracking error of the aerodynamic angle needs to be limited to achieve effective attitude control or high-accuracy tracking of trajectories,which is the so-called performance constraints.To this end,an attitude control method that meets the needs of PCA has been devised,based on constraint definition,coupled constraints handling,and control law design.Firstly,mathematical descriptions of the security constraints,performance constraints,and control constraints are given.Secondly,two treatment methods,coupled command filter and coupled funnel control are proposed for the aerodynamic angle coupled constraint problem.Finally,based on Nonlinear Dynamic Inverse(NDI)design,the coupled funnel controller is designed and validated by simulation for two typical mission scenarios,high-altitude penetration and low-altitude surprise defence.The proposed control method not only satisfies the security and performance constraints of STAV attitude control but also is highly robust.

Accelerated Landweber iteration based control allocation for fault tolerant control of reusable launch vehicle

This paper presents a novel Fault Tolerant Control(FTC)scheme based on accelerated Landweber iteration and redistribution mechanism for a horizontal takeoff horizontal landing reusable launch vehicle(RLV).First,an adaptive law based on fixed-time non-singular fast terminal sliding mode control(NFTSMC),which focuses on the attitude tracking controller design for RLV in the presence of model couplings,parameter uncertainties and external disturbances,is proposed to produce virtual control command.On this basis,a novel Control Allocation(CA)based on accelerated Landwber iteration is presented to realize proportional allocation of virtual control command among the actuators according to the effective gain as well as the distance from the current position of actuator to corresponding saturation limit.Meanwhile a novel redistribution mechanism is introduced to redistribute oversaturated command among healthy actuators(non-faulty or redundant).The proposed method can be applied to a real-time FTC system so that the controller reconfiguring is not required in case of actuator faults.Finally,the effectiveness of the proposed method is demonstrated by numerical simulations.

A Modified Direct Allocation Algorithm with Application to Redundant Actuators

Control allocation considers the problem of controlling instruction distribution for control systems with multiple and redundant actuators. This paper focuses on the direct allocation method, making the time requirement of the algorithm analogous compared with modified pseudoinverse redistribution methods, linear programming methods solved by simplex method, and sub-gradient optimization method. To reduce off-line computations of constructing the attainable moment set of actuators, a new approach based on the null space of the control effectiveness matrix is proposed, which is superior when the number of actuators is less than 10 compared with traditional method. To decrease on-line computations, an improvement method of searching the facet that is aligned with the desired moment is presented, shortening the search time by checking only the facets that lie around the desired moment. To find such facets, the vertices of the attainable moment set are normalized and saved during off-line computations. Simulation results show that at least 32.22% of off-line computation time would be saved using null space-based construction when the number of actuators is less than 10. In on-line computations, the modified method performs superiorly compared with the three aforementioned methods. Furthermore, it may solve the problem of control allocation efficiently when a remarkable large number of redundant actuators are configured.

Anti-disturbance attitude control of combined spacecraft with enhanced control allocation scheme

In this paper, we propose a novel anti-disturbance attitude control law for combined spacecraft with an improved closed-loop control allocation scheme. More specifically, a saturated approach is adopted to guarantee the global asymptotic stability under control input saturation.To enhance the robustness of the system, a nonlinear disturbance observer is constructed to compensate the disturbances caused by inertial parameter uncertainty and unmodeled dynamics. Next,the quadratic programming algorithm is used to obtain an optimal open-loop control allocation scheme, where both energy consumption and actuator saturation have been considered in the allocation of the virtual control command. Then, a modified closed-loop control allocation scheme is proposed to reduce the allocation error under the actuator uncertainty. Finally, stability analysis of the closed-loop system with the proposed allocation scheme is provided. Simulation results confirm the effectiveness of the proposed control scheme.

Event-triggered fault-tolerant consensus control with control allocation in leader-following multi-agent systems

Event-triggered consensus in leader-following multi-agent systems with actuator fault is considered in this paper, in which the fault investigated can be multiplicative fault and outage fault. An event-triggered mechanism is utilized to relieve the communication burden of the interconnected system. Then, control allocation is proposed to solve actuator fault in the multi-agent systems for the first time. Compared with the existing fault-tolerant methods, the proposed method can guarantee that the consensus errors converge to zero asymptotically without the traditional rank assumption. Meanwhile, the Zeno behavior of the event-triggered system is proved to be avoided. Simulation results are also provided to verify the effectiveness of the proposed method.

Closed-loop dynamic control allocation for aircraft with multiple actuators

A closed-loop control allocation method is proposed for a class of aircraft with multiple actuators. Nonlinear dynamic inversion is used to design the baseline attitude controller and derive the desired moment increment. And a feedback loop for the moment increment produced by the deflections of actuators is added to the angular rate loop, then the error between the desired and actual moment increment is the input of the dynamic control allocation. Subsequently, the stability of the closed-loop dynamic control allocation system is analyzed in detail. Especially, the closedloop system stability is also analyzed in the presence of two types of actuator failures： loss of effectiveness and lock-in-place actuator failures, where a fault detection subsystem to identify the actuator failures is absent. Finally, the proposed method is applied to a canard rotor/wing （CRW） aircraft model in fixed-wing mode, which has multiple actuators for flight control. The nonlinear simulation demonstrates that this method can guarantee the stability and tracking performance whether the actuators are healthy or fail.

Effective control allocation using hierarchical multi-objective optimization for multi-phase flight

For different flight phases in an overall flight mission,different control and allocation preferences should be pursued considering lift,drag or maneuverability characteristics.The multi-objective flight control allocation problem for a multi-phase flight mission is studied.For an overall flight mission,different flight phases namely climbing,cruise,maneuver and gliding phases are defined.Firstly,a multi-objective control allocation problem considering drag,lift or control energy preference is constructed.Secondly,considering different control preferences at different flight phases,the analytic hierarchical process method is used to construct a comprehensive performance index from different objectives such as lift or drag preferences.The active set based dynamic programming optimization method is used to solve the real-time optimization problem.For the validation,the Innovative Control Effector(ICE)tailless aircraft nonlinear model and the angular acceleration measurements based adaptive Incremental Backstepping(IBKS)are used to construct the validation platform.Finally,an overall flight mission is simulated to demonstrate the efficiency of the proposed multi-phase and multi-objective flight control allocation method.The results show that the comprehensive performance index for different phases,which are determined from the Analytic Hierarchy Process(AHP)method,can suitably satisfy the preference requirements for different flight phases.

Guaranteed feasible control allocation using model predictive control

This paper proposes a guaranteed feasible control allocation method based on the model predictive control. Feasible region is considered to guarantee the determination of the desired virtual control signal using the pseudo inverse methodology and is described as a set of constraints of an MPC problem. With linear models and the given constraints, feasible region defines a convex polyhedral in the virtual control space. In order to reduce the computational time, the polyhedral can be approximated by a few axis alig ned hypercubes. Employing the MPC with rectangular constraints substantially reduces the computational complexity .In two dimensions, the feasible region can be approximated by a few rectangles of the maximum area using numerical geometry techniques which are considered as the constraints of the MPC problem. Also, an active MPC is defined as the controller to minimize the cost function in the control horizon. Finally, several simulation examples are employed to illustrate the effectiveness of the proposed techniques.